class_docstr: Dataset used to parallelize the transformation of the dataset via a DataLoader
class_docstr_tok: ["Dataset","used","to","parallelize","the","transformation","of","the","dataset","via","a","DataLoader"]
docstr: Extract the middle frame out of a video clip.
docstr_tok: ["Extract","the","middle","frame","out","of","a","video","clip","."]
code: def _extract_middle_frame(file_path: str) -> Optional[Image.Image]:
      """
      Extract the middle frame out of a video clip.
      """
      with av.open(file_path) as container:
          nb_frames = container.streams.video[0].frames
          vid_stream = container.streams.video[0]
          for i, frame in enumerate(container.decode(vid_stream)):
              if i - 1 == nb_frames // 2:
                  return frame.to_image()
          return None
  
file_path: vissl/extra_scripts/datasets/create_ucf101_data_files.py
imports: import argparse
  import os
  import ssl
  from contextlib import contextmanager
  from typing import List, Optional, Tuple
  from PIL import Image
  from torch.utils.data import DataLoader
  from torchvision.datasets.utils import download_url, extract_archive
  from tqdm import tqdm
label_desc: Use image node_id 3 for calling the _ExtractMiddleFrameDataset obj's underlying member method code with example usage: obj._extract_middle_frame(file_path) and returns: None, frame